Generally, people have been using a multitude of different methods and devices to track dietary food consumption and fitness. These methodologies include systems for counting calories, tracking points, excluding or limiting certain types of foods, etc. These systems can also include fitness tracking for estimating how many calories the user may have burned in relation in estimated caloric intake. Overall, the widespread use of smartphones, tablets, and other mobile devices has revolutionized the way in which many people monitor and guide their food consumption habits.
However, these devices, systems, applications, and methodologies experience several shortcomings. In particular, the current diet monitoring technologies experience several shortcomings based in part on shortcomings in the object imaging and characterization technologies. The most popular food related tracking and recording applications are intended for use with a smartphone, allowing users to download the application, set up a user account in which the user enters their goals for weight loss, amount of exercise, macronutrient intake, blood pressure, sleep patterns, etc. Conventional applications require the user to manually log their food intake and exercise through self-reporting based on the selections from a network database of foods and associated values. Using the manually reported information, diet monitoring applications typically output nutritional information based on the user input. Many users find the manual entry of foods difficult, bothersome, and confusing, which leads to users failing to use the application consistently or correctly for long periods of time and in turn reducing the effectiveness of such existing technology.
Additionally, several handheld consumer spectrometer devices, which use spectrometry to analyze the chemical composition of food (primarily to identify allergens) are more common. However these handheld spectrometer devices are not integrated with any means of automatically determining the volume of the portions, or to automatically separate and isolate the various foods on a plate to automatically analyze an entire meal. The spectrometers require users to manually enter their dietary intake and exercise to monitor their calorie and nutrient intake. Additionally, the handheld spectrometers represent another device for users carry around for use when they need to capture chemical compositions of food items within their meals, in addition to other common devices such as smartphones. Finally, the handheld consumer spectrometer devices are expensive. There is a need for system that provides a comprehensive means for the user to capture image data of one or more objects, such as food items, and automatically assess characteristics of the one or more objects and use the determined characteristics to automatically implement desired processes, such as the obtaining, tracking and monitoring of caloric and nutrient intake, in a more cost effective manner that leverages pre-existing user devices such as smartphones in a more robust manner.